Swim five Python: shades of copy for a variety of data types

First, the numbers and strings

For the numbers and strings, the assignment, shallow vs. deep copy meaningless, because it always points to the same memory address.

import copy
# ######### 数字、字符串 #########
n1 = 123
# n1 = "i am alex age 10"
print(id(n1))
# ## 赋值 ##
n2 = n1
print(id(n2))
# ## 浅拷贝 ##
n2 = copy.copy(n1)
print(id(n2))

# ## 深拷贝 ##
n3 = copy.deepcopy(n1)
print(id(n3))

 

 Second, other basic data types

For purposes of dictionaries, tuples, lists, assignment, deep and shallow copy copy, change its memory address is different.

1, the assignment

Assignment , just create a variable that points to the original memory address, such as:

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n2 = n1

 

2, shallow copy

Shallow copy , only the first layer creates the additional data in memory

import copy

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n3 = copy.copy(n1)

 

3, deep copy 

Deep copy , all of the data in the memory to recreate a copy (excluding the last one, namely: the internal optimization python strings and numbers)

import copy

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n4 = copy.deepcopy(n1)